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Sangmi Kim

Showing results (31-40 of 90) with videos related to

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Computers, Informatics, Nursing : CIN|November 29, 2022
Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language ProcessingYuan-Chi Yang, Angel Xie, Sangmi Kim, et al.
Menopause (New York, N.Y.)|November 22, 2018
Decreasing menopausal symptoms of Asian American breast cancer survivors through a technology-based information and coaching/support programEun-Ok Im, Sangmi Kim, Chiyoung Lee, et al.
Asia-Pacific Journal of Public Health|April 27, 2012
Unequal geographic distribution of life expectancy in SeoulSangmi Kim, Seonju Yi, Meekyung Kim, et al.
Plos One|September 23, 2015
Non-Steroidal Anti-Inflammatory Drug Use and Genomic DNA Methylation in BloodLauren E Wilson, Sangmi Kim, Zongli Xu, et al.
Advances in Peer-Led Learning|June 26, 2024
Peer Facilitation: Accelerating Individual, Community, and Societal ChangeAthena D F Sherman, Monique Balthazar, Sangmi Kim, et al.
Computers, Informatics, Nursing : CIN|June 22, 2018
What to Consider in a Culturally Tailored Technology-Based Intervention?Eun-Ok Im, Wonshik Chee, Yun Hu, et al.
Clinical Pharmacology and Therapeutics|November 27, 2020
Drug-Drug Interaction Surveillance Study: Comparing Self-Controlled Designs in Five Empirical Examples in Real-World DataKatsiaryna Bykov, Hu Li, Sangmi Kim, et al.
Clinical Epidemiology|June 7, 2023
Validation of an Algorithm to Identify Venous Thromboembolism in Health Insurance Claims Data Among Patients with Rheumatoid ArthritisSangmi Kim, Carolyn Martin, John White, et al.
BMC Pregnancy and Childbirth|June 22, 2024
Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning modelSangmi Kim, Patricia A Brennan, George M Slavich, et al.
BMC Pregnancy and Childbirth|September 2, 2025
Multidimensional predictors of preterm birth risk among black and white primiparous women in the U.S.: insights from machine learningSangmi Kim, Zahra Barandouzi, Sophie Grant, et al.
Pageof 9

Showing results (31-40 of 90) with videos related to

Sort By:
Pageof 9
Computers, Informatics, Nursing : CIN|November 29, 2022
Automatic Detection of Twitter Users Who Express Chronic Stress Experiences via Supervised Machine Learning and Natural Language ProcessingYuan-Chi Yang, Angel Xie, Sangmi Kim, et al.
Menopause (New York, N.Y.)|November 22, 2018
Decreasing menopausal symptoms of Asian American breast cancer survivors through a technology-based information and coaching/support programEun-Ok Im, Sangmi Kim, Chiyoung Lee, et al.
Asia-Pacific Journal of Public Health|April 27, 2012
Unequal geographic distribution of life expectancy in SeoulSangmi Kim, Seonju Yi, Meekyung Kim, et al.
Plos One|September 23, 2015
Non-Steroidal Anti-Inflammatory Drug Use and Genomic DNA Methylation in BloodLauren E Wilson, Sangmi Kim, Zongli Xu, et al.
Advances in Peer-Led Learning|June 26, 2024
Peer Facilitation: Accelerating Individual, Community, and Societal ChangeAthena D F Sherman, Monique Balthazar, Sangmi Kim, et al.
Computers, Informatics, Nursing : CIN|June 22, 2018
What to Consider in a Culturally Tailored Technology-Based Intervention?Eun-Ok Im, Wonshik Chee, Yun Hu, et al.
Clinical Pharmacology and Therapeutics|November 27, 2020
Drug-Drug Interaction Surveillance Study: Comparing Self-Controlled Designs in Five Empirical Examples in Real-World DataKatsiaryna Bykov, Hu Li, Sangmi Kim, et al.
Clinical Epidemiology|June 7, 2023
Validation of an Algorithm to Identify Venous Thromboembolism in Health Insurance Claims Data Among Patients with Rheumatoid ArthritisSangmi Kim, Carolyn Martin, John White, et al.
BMC Pregnancy and Childbirth|June 22, 2024
Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning modelSangmi Kim, Patricia A Brennan, George M Slavich, et al.
BMC Pregnancy and Childbirth|September 2, 2025
Multidimensional predictors of preterm birth risk among black and white primiparous women in the U.S.: insights from machine learningSangmi Kim, Zahra Barandouzi, Sophie Grant, et al.
Pageof 9